Edge computing emerges as an innovative platform for services requiring low latency decision making. Its success partly depends on the existence of efficient data management systems. We consider that knowledge graph management systems have a key role to play in this context due to their data integration and reasoning features. In this paper, we present SuccinctEdge, a compact, decompression-free, self-index, in-memory RDF store that can answer SPARQL queries, including those requiring reasoning services associated to some ontology. We provide details on its design and implementation before demonstrating its efficiency on real-world and synthetic datasets.
@article{arxiv.2012.07108,
title = {Knowledge Graph Management on the Edge},
author = {Weiqin Xu and Olivier Curé and Philippe Calvez},
journal= {arXiv preprint arXiv:2012.07108},
year = {2020}
}